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Commit db2e0fab authored by Andreas Marek's avatar Andreas Marek
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Licensing and copyright terms for the ELPA library:
ELPA Consortium (2011)
****
Copyright of the original code rests with the authors inside the ELPA
consortium. The copyright of any additional modifications shall rest
with their original authors, but shall adhere to the licensing terms
set forth below.
****
The code is distributed under the terms of the GNU Lesser General Public
License version 3 (LGPL). The full text can be found in the file "lgpl.txt"
in this repository. "lgpl.txt" makes reference to the GPL v3, which can also
be found in this repository ("gpl.txt").
****
ELPA reflects a substantial effort on the part of the original
ELPA consortium, and we ask you to respect the spirit of the
license that we chose: i.e., please contribute any changes you
may have back to the original ELPA library distribution, and keep
any derivatives of ELPA under the same license that we chose for
the original distribution, the GNU Lesser General Public License.
When in doubt, talk to us. What we would like to ensure is that the ELPA
code can be used as needed, while providing a strong incentive for
others to contribute their modifications back to the original development.
****
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GNU LESSER GENERAL PUBLIC LICENSE
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Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
This version of the GNU Lesser General Public License incorporates
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License, supplemented by the additional permissions listed below.
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ELPA_development_version/README deleted 100644 → 0
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Welcome to the git-based distribution of the ELPA eigensolver library.
If you are reading this file, you have obtained the ELPA library
through the git repository that hosts the source code and also allows
you to contribute improvements to the project if necessary.
In your use of ELPA, please respect the copyright restrictions
found below and in the "COPYING" directory in this repository. In a
nutshell, if you make improvements to ELPA, copyright for such
improvements remains with you, but we request that you relicense any
such improvements under the same exact terms of the (modified) LGPL v3
that we are using here. Please do not simply absorb ELPA into your own
project and then redistribute binary-only without making your exact
version of the ELPA source code (unmodified or MODIFIED) available as
well.
*** Citing:
A description of some algorithms present in ELPA can be found in:
T. Auckenthaler, V. Blum, H.-J. Bungartz, T. Huckle, R. Johanni,
L. Kr\"amer, B. Lang, H. Lederer, and P. R. Willems,
"Parallel solution of partial symmetric eigenvalue problems from
electronic structure calculations",
Parallel Computing 37, 783-794 (2011).
doi:10.1016/j.parco.2011.05.002.
Please cite this paper when using ELPA. We also intend to publish an
overview description of the ELPA library as such, and ask you to
make appropriate reference to that as well, once it appears.
*** Copyright:
Copyright of the original code rests with the authors inside the ELPA
consortium. The code is distributed under the terms of the GNU Lesser General
Public License version 3 (LGPL).
Please also note the express "NO WARRANTY" disclaimers in the GPL.
Please see the file "COPYING" for details, and the files "gpl.txt" and
"lgpl.txt" for further information.
*** Using ELPA:
ELPA is designed to be compiled (Fortran) on its own, to be later
linked to your own application. In order to use ELPA, you must still
have a set of separate libraries that provide
- Basic Linear Algebra Subroutines (BLAS)
- Lapack routines
- Basic Linear Algebra Communication Subroutines (BLACS)
- Scalapack routines
- a working MPI library
Appropriate libraries can be obtained and compiled separately on many
architectures as free software. Alternatively, pre-packaged libraries
are usually available from any HPC proprietary compiler vendors.
For example, Intel's ifort compiler contains the "math kernel library"
(MKL), providing BLAS/Lapack/BLACS/Scalapack functionality. (except on
Mac OS X, where the BLACS and Scalapack part must still be obtained
and compiled separately).
A very usable general-purpose MPI library is OpenMPI (ELPA was tested
with OpenMPI 1.4.3 for example). Intel MPI seems to be a very well
performing option on Intel platforms.
Examples of how to use ELPA are included in the accompanying
test_*.f90 subroutines in the "test" directory. A Makefile in also
included as a minimal example of how to build and link ELPA to any
other piece of code.
*** Structure of this repository:
* README file - this file. Please also consult the ELPA Wiki, and
consider adding any useful information that you may have.
* COPYING directory - the copyright and licensing information for ELPA.
* src directory - contains all the files that are needed for the
actual ELPA subroutines. If you are attempting to use ELPA in your
own application, these are the files which you need.
- elpa1.f90 contains routines for the one-stage solver,
The 1 stage solver (elpa1.f90) can be used standalone without elpa2.
- elpa2.f90 - ADDITIONAL routines needed for the two-stage solver
elpa2.f90 requires elpa1.f90 and a version of elpa2_kernels.f90, so
always compile them together.
- elpa2_kernels.f90 - optimized linear algebra kernels for ELPA.
This file is a generic version of optimized linear algebra kernels
for use with the ELPA library. The standard elpa2_kernels.f90 runs
on every platform but it is optimized for the Intel SSE instruction
set. Best perfomance is achieved with the Intel ifort compiler and
compile flags -O3 -xSSE4.2
For optimum performance on special architectures, you may wish to
investigate whether hand-tuned versions of this file give additional
gains. If so, simply remove elpa2_kernels.f90 from your compilation
and replace with the version of your choice. It would be great if
you could contribute such hand-tuned versions back to the
repository. (LGPL requirement for redistribution holds in any case)
- elpa2_kernels_bg.f90
Example of optimized ELPA kernels for the BlueGene/P
architecture. Use instead of the standard elpa2_kernels.f90
file. elpa2_kernels_bg.f90 contains assembler instructions for the
BlueGene/P processor which IBM's xlf Fortran compiler can handle.
- elpa_qr directory (development version only)
This directory contains routines for an alternative implementation
of the QR-decomposition of "tall and skinny" matrices, which is
needed for the reduction to banded form. The usage of this
alternative implementation can be switched on and off by setting
the variable "which_qr_decomposition" in elpa2.f90 (default = on).
* test directory
- Contains the Makefile that demonstrates how to compile and link to
the ELPA routines
- All files starting with test_... are for demonstrating the use
of the elpa library (but not needed for using it).
- The test_* programs build their own random matrices, solve the eigenvalue
problem and write timings.
There are three parameters that control the test_* programs:
- na = matrix dimension
- nev = number of eigenvalue / eigenvector pairs that is actually needed
- nblk = algorithmic block size, usually 16, 32 or 64
(important - do not set to unreasonable values)
These input parameters are set to default values na=4000, nev=1500, nblk=16
in the header of each source file test*.f90 .
Optionally, they can be controlled at runtime by supplying an input file
called 'test_parameters.in'.
This file can contain any or no lines at all (input values not specified in
'test_parameters.in' will be set to default values).
The format of test_parameters.in is simple, for instance:
na 8000
nev 6000
nblk 32
to change all values. Order of lines does not matter.
- All test programs solve a eigenvalue problem and check the correctnes
of the result by evaluating || A*x - x*lamba || and checking the
orthogonality of the eigenvectors
test_real Real eigenvalue problem, 1 stage solver
test_real_gen Real generalized eigenvalue problem, 1 stage solver
test_complex Complex eigenvalue problem, 1 stage solver
test_complex_gen Complex generalized eigenvalue problem, 1 stage solver
test_real2 Real eigenvalue problem, 2 stage solver
test_complex2 Complex eigenvalue problem, 2 stage solver
- There are two programs which read matrices from a file, solve the
eigenvalue problem, print the eigenvalues and check the correctness
of the result (all using elpa1 only)
read_real for the real eigenvalue problem
read_real_gen for the real generalized eigenvalue problem
A*x - B*x*lambda = 0
read_real has to be called with 1 command line argument (the file
containing the matrix). The file must be in ASCII (formatted) form.
read_real_gen has to be called with 3 command line arguments. The
first argument is either 'asc' or 'bin' (without quotes) and
determines the format of the following files. 'asc' refers to ASCII
(formatted) and 'bin' to binary (unformatted). Command line
arguments 2 and 3 are the names of the files which contain matrices
A and B.
The structure of the matrix files for read_real and read_real_gen
depends on the format of the files:
* ASCII format (both read_real and read_real_gen):
The files must contain the following lines:
- 1st line containing the matrix size
- then following the upper half of the matrix in column-major
(i.e. Fortran) order, one number per line:
a(1,1)
a(1,2)
a(2,2)
...
a(1,i)
...
a(i,i)
...
a(1,n)
...
a(n,n)
* Binary format (read_real_gen only):
The files must contain the following records:
- 1st record: matrix size (type integer)
- 2nd record: a(1,1)
- 3rd record: a(1,2) a(2,2)
- ...
- ... a(1,i) ... a(i,i)
- ...
- ... a(1,n) ... a(n,n)
The type of the matrix elements a(i,j) is real*8.
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ELPA generally uses BLAS-Routines for all compute intensive work
so that the performance of ELPA mainly depends on the quality of
the BLAS implementation used when linking.
The only exception is the backtransformation of the eigenvectors
for the 2-stage solver (ELPA2). In this case BLAS routines cannot
be used effectively due to the nature of the problem.
The compute intensive part of the backtransformation of ELPA2
has been put to a file of its own (elpa2_kernels.f90) so that
this can be replaced by hand tailored, optimized code for
specific platforms.
Currently we offer the following alternatives for the ELPA2 kernels:
* elpa2_kernels.f90 - The generic FORTRAN version of the ELPA2 kernels
which should be useable on every platform.
It contains some hand optimizations (loop unrolling)
in the hope to get optimal code from most FORTRAN
compilers.
* elpa2_kernels_simple.f90 - Plain and simple version of elpa2_kernels.f90.
Please note that we observed that some compilers get
get confused by the hand optimizations done in
elpa2_kernels.f90 and give better performance
with this version - so it is worth to try both!
* elpa2_kernels_bg.f90 - Fortran code enhanced with assembler calls
for the IBM BlueGene/P
* elpa2_tum_kernels_*.c - Optimized intrinisic code for x86_64
systems (i.e. Intel/AMD architecture)
using SSE2/SSE3 operations.
(Use gcc for compiling as Intel compiler generates slower code!)
So which version should be used?
================================
* On x86_64 systems (i.e. almost all Intel/AMD systems) or on the IBM BlueGene/P
you should get the optimal performance using the optimized intrinsics/assembler versions
in elpa2_tum_kernels_*.c or elpa2_kernels_bg.f90 respectively.
* If you don't compile for one of these systems or you don't like to use assembler
for any reason, it is likely that you are best off using elpa2_kernels.f90.
Make a perfomance test with elpa2_kernels_simple.f90, however, to check if
your compiler doesn't get confused by the hand optimizations.
* If you want to develop your own optimized kernels for you platform, it is
easier to start with elpa2_kernels_simple.f90.
Don't let you confuse from the huge code in elpa2_kernels.f90, the mathemathics
done in the kernels is relatively trivial.
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! This file is part of ELPA.
!
! The ELPA library was originally created by the ELPA consortium,
! consisting of the following organizations:
!
! - Rechenzentrum Garching der Max-Planck-Gesellschaft (RZG),
! - Bergische Universität Wuppertal, Lehrstuhl für angewandte
! Informatik,
! - Technische Universität München, Lehrstuhl für Informatik mit
! Schwerpunkt Wissenschaftliches Rechnen ,
! - Fritz-Haber-Institut, Berlin, Abt. Theorie,
! - Max-Plack-Institut für Mathematik in den Naturwissenschaftrn,
! Leipzig, Abt. Komplexe Strukutren in Biologie und Kognition,
! and
! - IBM Deutschland GmbH
!
!
! More information can be found here:
! http://elpa.rzg.mpg.de/
!
! ELPA is free software: you can redistribute it and/or modify
! it under the terms of the version 3 of the license of the
! GNU Lesser General Public License as published by the Free
! Software Foundation.
!
! ELPA is distributed in the hope that it will be useful,
! but WITHOUT ANY WARRANTY; without even the implied warranty of
! MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
! GNU Lesser General Public License for more details.
!
! You should have received a copy of the GNU Lesser General Public License
! along with ELPA. If not, see <http://www.gnu.org/licenses/>
!
! ELPA reflects a substantial effort on the part of the original
! ELPA consortium, and we ask you to respect the spirit of the
! license that we chose: i.e., please contribute any changes you
! may have back to the original ELPA library distribution, and keep
! any derivatives of ELPA under the same license that we chose for
! the original distribution, the GNU Lesser General Public License.
!
!
! --------------------------------------------------------------------------------------------------
!
! This file contains the compute intensive kernels for the Householder transformations.
!
! *** Special IBM BlueGene/P version with BlueGene assembler instructions in Fortran ***
!
! Copyright of the original code rests with the authors inside the ELPA
! consortium. The copyright of any additional modifications shall rest
! with their original authors, but shall adhere to the licensing terms
! distributed along with the original code in the file "COPYING".
!
! --------------------------------------------------------------------------------------------------
subroutine single_hh_trafo_complex(q, hh, nb, nq, ldq)
implicit none
integer, intent(in) :: nb, nq, ldq
complex*16, intent(inout) :: q(ldq,*)
complex*16, intent(in) :: hh(*)
integer i
! Safety only:
if(mod(ldq,4) /= 0) STOP 'double_hh_trafo: ldq not divisible by 4!'
! Do the Householder transformations
! Always a multiple of 4 Q-rows is transformed, even if nq is smaller
do i=1,nq-8,12
call hh_trafo_complex_kernel_12(q(i,1),hh, nb, ldq)
enddo
! i > nq-8 now, i.e. at most 8 rows remain
if(nq-i+1 > 4) then
call hh_trafo_complex_kernel_8(q(i,1),hh, nb, ldq)
else if(nq-i+1 > 0) then
call hh_trafo_complex_kernel_4(q(i,1),hh, nb, ldq)
endif
end
! --------------------------------------------------------------------------------------------------
subroutine hh_trafo_complex_kernel_12(q, hh, nb, ldq)
implicit none
integer, intent(in) :: nb, ldq
complex*16, intent(inout) :: q(ldq,*)
complex*16, intent(in) :: hh(*)
complex*16 x1, x2, x3, x4, x5, x6, x7, x8, x9, xa, xb, xc
complex*16 h1, tau1
integer i
x1 = q(1,1)
x2 = q(2,1)
x3 = q(3,1)
x4 = q(4,1)
x5 = q(5,1)
x6 = q(6,1)
x7 = q(7,1)
x8 = q(8,1)
x9 = q(9,1)
xa = q(10,1)
xb = q(11,1)
xc = q(12,1)
!DEC$ VECTOR ALIGNED
do i=2,nb
h1 = conjg(hh(i))
x1 = x1 + q(1,i)*h1
x2 = x2 + q(2,i)*h1
x3 = x3 + q(3,i)*h1
x4 = x4 + q(4,i)*h1
x5 = x5 + q(5,i)*h1
x6 = x6 + q(6,i)*h1
x7 = x7 + q(7,i)*h1
x8 = x8 + q(8,i)*h1
x9 = x9 + q(9,i)*h1
xa = xa + q(10,i)*h1
xb = xb + q(11,i)*h1
xc = xc + q(12,i)*h1
enddo
tau1 = hh(1)
h1 = -tau1
x1 = x1*h1
x2 = x2*h1
x3 = x3*h1
x4 = x4*h1
x5 = x5*h1
x6 = x6*h1
x7 = x7*h1
x8 = x8*h1
x9 = x9*h1
xa = xa*h1
xb = xb*h1
xc = xc*h1
q(1,1) = q(1,1) + x1
q(2,1) = q(2,1) + x2
q(3,1) = q(3,1) + x3
q(4,1) = q(4,1) + x4
q(5,1) = q(5,1) + x5
q(6,1) = q(6,1) + x6
q(7,1) = q(7,1) + x7
q(8,1) =